Information Technology & Social Media News

At DARPA's Electronics Resurgence Initiative 2019 in Michigan, Intel introduced a new neuromorphic computer capable of simulating 8 million neurons. Neuromorphic engineering, also known as neuromorphic computing, describes the use of systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system. Scientists at MIT, Perdue, Stanford, IBM, HP, and elsewhere have pioneered pieces of full-stack systems, but arguably few have come closer than Intel when it comes to tackling one of the longstanding goals of neuromorphic research — a supercomputer a thousand times more powerful than any today. Case in point? Today during the Defense Advanced Research Projects Agency’s (DARPA) Electronics Resurgence Initiative 2019 summit in Detroit, Michigan, Intel unveiled a system codenamed “Pohoiki Beach,” a 64-chip computer capable of simulating 8 million neurons in total. Intel Labs managing director Rich Uhlig said Pohoiki Beach will be made available to 60 research partners to “advance the field” and scale up AI algorithms like spare coding and path planning. “We are impressed with the early results demonstrated as we scale Loihi to create more powerful neuromorphic systems. Pohoiki Beach will now be available to more than 60 ecosystem partners, who will use this specialized system to solve complex, compute-intensive problems,” said Uhlig. Pohoiki Beach packs 64 128-core, 14-nanometer Loihi neuromorphic chips, which were first detailed in October 2017 at the 2018 Neuro Inspired Computational Elements (NICE) workshop in Oregon. They have a 60-millimeter die size and contain over 2 billion transistors, 130,000 artificial neurons, and 130 million synapses, in addition to three managing Lakemont cores for task orchestration. Uniquely, Loihi features a programmable microcode learning engine for on-chip training of asynchronous spiking neural networks (SNNs) — AI models that incorporate time into their operating model, such that components of the model don’t process input data simultaneously. This will be used for the implementation of adaptive self-modifying, event-driven, and fine-grained parallel computations with high efficiency.
Via Philippe J DEWOST

Magic Leap raised $794 million in new funding and CEO Rony Abovitz posted a blog suggesting the secretive company is moving closer toward a product, writing “we are setting up supply chain operations, manufacturing.”

Chinese e-commerce company Alibaba led the round and Joe Tsai, Alibaba’s Executive Vice Chairman, is getting a seat on the board. The announcement roughly confirms a December report suggesting the company was raising money in this ballpark.

The Series C round puts the Florida startup’s funding to date close to $1.4 billion.

 

Magic Leap also seems to have named its technology “Mixed Reality Lightfield” with subtle language in the blog post linked above that might be commentary about current VR technology, which isn’t able to perfectly reproduce what your eyes see in the real world.

“It comes to life by following the rules of the eye and the brain, by being gentle, and by working with us, not against us,” Abovitz wrote about the company’s technology. “By following as closely as possible the rules of nature and biology.”

Abovitz previously suggested Rift-like VR headsets have a history of “issues that near-eye stereoscopic 3d may cause” and that “we have done an internal hazard and risk analysis….on the spectrum of hazards that may occur to a wide array of users.”

Via Philippe J DEWOST

Cars are no longer what they seem to be. On-board computers and their algorithms have invaded all organs, making cars better, but also more susceptible to hacks and invasions of privacy.

Having driven Route 85 between Cupertino and Mountain View a few thousand times, I’m familiar with every rift and gap in the concrete, every subtle camber shift as I follow an habitual, gradual arc through curves and lane changes. Some early Chevrolet episodes aside, I’m behind the wheel of a European vehicle, silent, good lungs, surefooted, precise, the kind of car that translates the driver’s steering motion into a smooth trajectory, no ifs or buts, no need for correction as the suspension takes its time to settle. After 31 years of driving this pleasant road, the feeling doesn’t get old.

A few weeks ago, I drove the familiar route in a new vehicle freshly delivered from Sindelfingen. Something is wrong: The first curve line is “dirty”, it lacks Germanic rigor. At the next curve the steering wheel argues with me, politely but clearly demanding a different trajectory.

When I get back home I look around the dashboard and notice two red indicators that had been hidden by the steering wheel while I was driving. The walkthrough tech at the dealership had set the vessel to autopilot. In retrospect, I should have seen the argumentative steering coming: I had ordered the autopilot and other geeky features that were unknown when I bought my previous chariot just five years ago. On the road, the autopilot had interpreted my steering ‘optimizations’ as daydreaming lane drift and had stepped in to keep me in line.

I disconnect the autopilot and go for a drive; the familiar pleasant feeling returns.

In a 1957 essay about the Citroën DS (pronounced “Déesse”, goddess) Roland Barthes hailed the modern car as…

“…the exact equivalent of the great Gothic cathedrals: I mean the supreme creation of an era, conceived with passion by unknown artists…it excites interest less by its substance than by the junction of its components. ”

The striving, energetic copulation of the arts and technologies, the ‘junction of components’ has continued. Cars are now nearly completely penetrated by automation and algorithms.

Via Philippe J DEWOST